Triple

T14302639
Position Surface form Disambiguated ID Type / Status
Subject Meppen E354605 entity
Predicate nearbyCity P350 FINISHED
Object Papenburg E231594 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Papenburg | Statement: [Meppen, nearbyCity, Papenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Papenburg
Context triple: [Meppen, nearbyCity, Papenburg]
  • A. Papenburg chosen
    Papenburg is a German town in Lower Saxony best known for its historic canals and its large Meyer Werft shipyard, one of the world’s leading builders of cruise ships.
  • B. Ochtrup
    Ochtrup is a small town in the Münster region of North Rhine-Westphalia in western Germany, known for its textile industry and designer outlet center.
  • C. Bentheim
    Bentheim is a historical county in Lower Saxony, Germany, known for its Reformed Protestant heritage and the former County of Bentheim.
  • D. Breckerfeld
    Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
  • E. Pinneberg
    Pinneberg is a town in northern Germany that serves as the administrative center of the district of the same name near Hamburg.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8278e17088190b328c5a9d4be74ff completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de717fc2348190bb6ba3109bd2871f completed April 14, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5504dc6c8190a4d8a5985632901d completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:12 a.m.